Fridays Academy: Gender and Macroeconomics

In the second strand of the literature referenced by Stotsky (2006), the sex of children in some cultures determines the amount of expenditure they receive. At the individual level, gender affects consumption of education, health and nutrition. In some cultures, women may spend more on male children, or in other cultures, this tendency may be reversed. For example, Schultz (1987) shows that price elasticities of demand for primary and secondary enrollment rates and for total years of school are higher for females than for males, and similarly for income elasticities for 90 countries. For India, Kingdon (2003) finds gender bias in the allocation of spending for education for boys. Moreover, she finds that spending on education is unlikely to take place for girls. Deaton (1989) using data from Cote d’Ivoire and Thailand finds no gender bias in medical and education spending in Cote d’Ivoire and a small and insignificant effect in favor of boys in Thailand. Across several developing countries, Glick, Saha and Younger (2004) find no discrimination in health care and education spending among boys and girls. While Alderman and Gertler (1997) using data from Pakistan note a gender bias in favor of boys with regard to demand for medical care.

A recent study in by Lewis and Lockheed (2007) further illustrates the extent and degree of the problem of girls’ exclusion from formal education.

In India, 37 percent of girls aged 7-14 belonging to the lower castes or tribes do not attend school, compared with 26 percent of majority girls of the same age. School attendance for tribal girls is 9 percentage points below that of tribal boys.

In Laos, Hill Tribe girls from rural communities complete fewer than two years of school, whereas majority Lao-Tai girls from urban communities complete eight years

In Guatemala, indigenous girls are the least likely to have ever enrolled in primary school and only 26 percent of indigenous non- Spanish-speaking girls complete primary school, compared with 62 percent of Spanish speaking girls.

In the Slovak Republic, only 9-percent of Roma girls compared with 54 percent of Slovak girls attend secondary school.

Macroeconomic policy that targets the exclusion of girls from education needs to be mindful of the price and income elasticities of demand for education. As noted by Stotsky (2006), relative price increases for education would adversely impact girls while price decreases would prove disproportionately beneficial to girls. Furthermore, the fact that there is a “higher income elasticity of demand for female education and health care implies that economic prosperity would disproportionately benefit females by expanding their access to these services, while recessions would have a disproportionately negative effect.” (Stotsky, 2006; p. 11) Sound macroeconomic policies that include an appropriately valued exchange rate – an overvalued exchange rate could raise the price of domestic goods and services, including education – are key to achieving investments in education and health.

Lewis and Lockheed (2007) suggest two avenues by which policy can ‘reach and teach’ excluded girls. First, investment is necessary to improve the quality of schooling by:

Making education policies more fair

Lewis and Lockheed (2007) note the unintentional consequences of some policies and cite the example of policies that require the use of a majority language in a school. In some cases, girls from an excluded group will not have had the exposure to the majority language that boys will have. Similarly, policies that require a single-sex school or co-education may limit girls’ opportunities. The authors cite the example of certain areas in Pakistan where only boys schools have been established and the tendency of some parents to restrict older girls’ education in co-educational schools.

Expanding schooling options

Lewis and Lockheed (2007) suggest a number of ways in which schooling options may be expanded for excluded groups, particularly girls and cite also country examples of expanded options. For example, in Brazil, Turkey, Bolivia and India preschool programs help in the transition to formal schooling for excluded groups; the community in Rajasthan, India selected and supervised teachers and also hired part-time workers to escort girls from excluded groups to school. Of course, radio, television and computers help to expand opportunities for excluded groups, especially girls who stay at home after primary school.

Improving the physical environment and instructional materials

Lewis and Lockheed (2007) note that research indicates that school quality in terms of infrastructure, absenteeism among teachers and school supplies matters more for excluded groups compared to children from mainstream families. Minority parents often have higher expectations for the quality of the school and even the gender of the teachers (Lewis and Lockheed, 2007).

And second, investment is necessary to create incentives for households to send girls to school. Although “evidence on what incentives might work is less clear and needs more focused evaluation” (Lewis and Lockheed, 2007; p. 19).

Offering conditional cash transfers

Transfers help households to put-off some of the education costs although such programs are often difficult to administer. Lewis and Lockheed (2007) refer to programs in Bangladesh, Ecuador, and Mexico that have been successful, although their impact on excluded groups was not assessed.

Offering scholarships and stipends for girls

Offering scholarships and stipends for girls to stay on in education after primary level is based on the same principle as the former incentive. Such a program in Bangladesh helped to double enrollment to twice the national average for females.

Introducing school feeding programs

Various school feeding programs have been shown to boost enrollment and attendance. However, such program in Kenya while successful in boosting attendance was found to have benefited boys more than girls, doing little to reduce the gender gap.

Analysis of expenditure on health, nutrition and education indicate that poor females are at a disadvantage compared to males and non-poor females. While the previous paragraphs outlined the discrimination that exists with regard to spending on well-being, the literature has also examined the gender effects of poverty at the level of the household and at the individual level.Lampietti and Stalker (2000) examine consumption expenditure and female poverty. Referencing over 60 Poverty Assessments carried out by the World Bank and other published and unpublished sources, Lampietti and Stalker (2003) find the following:

(i) Poor women have higher fertility rates, higher maternal mortality, lower birth weights, and less access to qualified or modern health care during pregnancy than non-poor women do – differences that are persistent in both low and middle-income countries.

(ii) There is no conclusive evidence that poor females are worse-off than poor males in terms of both food allocation and anthropometric status (i.e. a measure of past food intakes)

(iii) No systematic pattern emerges between low and middle-income countries for gender and education.

(iv) Based on 22 poverty assessments that included analysis of gender and education: (a) girls are worse off than boys in Djibouti, Niger, Kenya, Egypt, Yemen and Pakistan; (b) the gender gap is amplified below the poverty line in Bolivia, Cote d’Ivoire, Malawi, Zambia, Morocco, Algeria, Lao PDR and India but boys are worse off than girls in Mongolia and Lesotho; and; (c) the analysis is inconclusive or no difference exists in Nicaragua, Madagascar, Mauritania, Rwanda, Tanzania, and Sri Lanka.